This present invention relates to signal processing and more particularly, to signal reconstruction and for filter design for partial band reconstruction of a wideband channelizer.
Signal detection and reconstruction are areas of importance for military and commercial applications. In most signal intelligence schemes, the system attempts to analyze a wide bandwidth detected signal and then subdivide the wide bandwidth into smaller bands. The smaller bands are investigated for the signals of interest by examining the energy response.
The subchannels or bins contain regions of signal energy and the processing measures the power in the various bins to locate regions of interest that have significant detectable power levels. In one implementation the wideband detection bandwidth is converted into a frequency domain snapshot using Fast Fourier Transform (FFT) processing many times per second. The snapshots are aligned in time with the ability to revisit various stored frequency bins, and are in time with a time delay between each snapshot.
To focus on a particular narrow band signal of interest, a certain number of adjacent channels are recombined into a narrowband time domain stream of data that can be further processed. There have been various attempts to employ an inverse transform to the time domain within the window of bins that does not affect the output stream. Ideally, the signal intelligence community would like to perform the perfect partial reconstruction of the desired narrowband window with no distortion.
Cosine filter banks are used in the prior art, but generally these filters are used with real data and not complex data. The cosine filter banks generally employ the same filter on the analysis and synthesis side.
There are many digital receiver systems used in the vast telecommunications area, and the main purpose of these receivers is to extract information signals from the many other interfering signals and noise interference. One example of a receiver is the channelized receiver. A channelized receiver comprises an antenna and a radio frequency front end that intercept radio frequency energy and performs signal conditioning and down conversion to a convenient intermediate frequency (IF). There are a number of characteristics that increase the ability to intercept a radio frequency signal of interest. Namely, a broadband instantaneous frequency coverage, good sensitivity, large dynamic range, simultaneous signal detection, arbitration and parameter encoding, and fine frequency measurement.
One problem with high sensitivity, narrow band intercept receivers is tuning to receive a signal having an unknown frequency. Reducing the bandwidth of a receiver generally increases its sensitivity, but results in tuning difficulties because the narrow bandwidth must be more precisely centered with respect to the incoming signal. One way conventional radar intercept receiving systems have tried to eliminate this problem is to search for the unknown signal with a less sensitive wide band receiver, and, once having detected a signal, tune a narrow band receiver to the detected signal. As the signal-to-noise ratio of the unknown signal becomes lower, the more difficult it is to utilize this method. In addition, it is usually desirable to rapidly identify the unknown signal in order to quickly tune the narrow band receiver to that frequency. Accordingly, channelized receivers having a plurality of filters each defining a contiguous passband portion of a search bandwidth have been utilized to quickly identify a channel in which an unknown signal resides, this channel then being used to identify a tuning frequency for a narrow band receiver. However, as the dynamic range of an unknown input signal increases, it becomes more difficult to determine the frequency of the signal without the use of complicated and complex redundancy comparison circuitry which is required when strong input signals provide output signals of substantially equal magnitude at two or more of the channelizer filters.
In order to widen RF bandwidth and improve the probability of intercept, the channelized receiver uses a number of contiguous filters, called a filter bank, to sort the input signal into segments of predetermined frequency. An input signal with a certain frequency will fall into a certain filter, and by measuring the output of the filters, the input signal frequency is estimated. Channelization generally refers to the filtering, decimation, interpolation and frequency conversion of received signals. A channelizer divides a wide receiver frequency band into many narrow frequency xe2x80x9cbinsxe2x80x9d or channels, so that the receiver can and digitally process each individual channel separately. The channelizer can be used in conjunction with a parameter encoder. The parameter encoder characterizes each received RF signal in accordance with a predetermined set of parameters, such as frequency, pulse width, amplitude, time of arrival, type of modulation.
The analog channelized receiver is relatively expensive to fabricate because of the large number of filters required. In addition, the analog receiver size is bulky and the maintenance is difficult because it requires a large number of components. The digital channelized receiver requires a contiguous set of digital band pass filters with linear phase that cover the IF bandwidth. This coverage can be accomplished with a set of discrete digital filters, or the digital filter bank can also be effectively implemented by performing the short time Fourier transform which in effect performs the discrete Fourier transform on weighted and overlapped partitions of a collection of discrete time signals.
The short time Fourier transform complex modulates a low pass filter h(n) to form a uniform filter bank having one filter centered at each frequency bin of the fast Fourier transform. The low pass filter h(n) is, in effect, used to window the data. The established window slides across the data and then the discrete Fourier transform is calculated to give a frequency versus time output. Between successive fast Fourier transform calculations, M points are skipped which results in the output being decimated in time by M. It is also possible to generate a fine frequency digital channelized receiver by using an instantaneous frequency measurement algorithm. Such an instantaneous frequency measurement receiver uses the phase data generated by the short time Fourier transform filter bank to generate the fine frequency selection capability of the digital channelized receiver.
A prior art analog receiver system receives a radio frequency (RF) signal that is received by the antenna and then downconverted to an intermediate frequency (IF) by a RF front end. The RF front end typically comprises low noise amplifiers (LNAs) to boost the signal from the low reception power, filters to remove some of the noise, and mixers to downconvert to IF using a local oscillator signal. The receiver channelizer then extracts the desired channel. The channelizer generally has LNAs, mixers and filters. The selected channel is then processed at baseband by the receiver baseband unit to produce the received digital data stream.
In more state of the art receivers, there are more digital implementations than analog. Baseband processing generally has analog-to-digital conversion, digital filtering, decimation, equalization, demodulation, channel decoding, de-interleaving, data decoding, and timing extraction. In the case of multiple channels, the processing is performed in a similar fashion but the path is split to form multiple paths for each channel being processed with the digital interface being somewhere between the RF front end/back end and channelizer/de-channelizer blocks. This digitized implementation includes multistandard radio, wideband digital tuners, wideband radio or software defined radio.
Efficient digital channelizer/de-channelizer structures, that perform filtering, decimation/interpolation and frequency conversion, are important in terms of power consumption and die area on a per channel basis. One of the main goals of these structures is to integrate as many channels into a single Integrated Circuit (IC) as possible.
FIG. la depicts one approach to channelization of a prior art receiver 70 fur a single channel with an incoming Frequency Division Multiplexed (EDMA) signal 75. A local oscillator (LO) 85 of frequency a downconverts the amplified RF input 75 in the mixer 80 to generate an intermediate frequency (IF) 90. A bandpass filter 95 selects the desired channel and an analog-to-digital converter (ADC) 100 converts the resulting output to digital form by sampling the analog signal at an appropriate frequency. Generally, the sampling frequency is at least twice the channel bandwidth to satisfy the Nyquist requirement. The sampled digital data, x(n), is bandshifted digitally by mixer 105 and digital detector 110 by multiplying with a phasor exe2x88x9212xcfx80(kn/N) denoted by WNkn, where k denotes the channel selected by the receiver. The resulting signal is low-pass filtered using a digital low pass filter 115. For multiple channels contained in the received signal, then one receiver path is needed for each of the channels. Downsampling or decimation 117 is required at the output.
A different approach to digital channelization is shown in FIG. 1b, wherein a conventional polyphase approach is taken. There are M channels of bandwidth B that are received simultaneously in a FDMA signal 120. After M channels, each of bandwidth B, are passed through an analog BPF (not shown) they are output to an A/D converter 125 which samples at some rate that is at least equal to the Nyquist rate (2 MB) for a signal of bandwidth MB. In this example, the data is sampled at 2 NB where N is greater than or equal to M. The digital output x(n) is applied to a 2N pole 130 that distributes the input data x(n) to 2N filters 135. Each filter 135 is updated once every 2N points. Filters 135 perform the channel extraction function. The time series output of filters 135 is applied to respective inputs of an FFT processor 140 which processes the data once every 2N points to produce 2N complex outputs of which M outputs are chosen, each representing the bandshifted subchannel signal at B Hz, the update rate of FFT processor 140. Only M outputs of FFT processor 140 are required since the sample rate 2 NB, as mentioned, can be higher than the minimum required sample rate 2 MB.
The power of optimized filter banks has been extended from the early uses for compression of speech, images and video signals to digital communications. In particular, the optimization of filter banks using statistical models has yielded significant improvements in increasing signal detection in multi-user environments of limited bandwidth.
Referring to FIG. 2a, a standard M-channel filter bank is shown with the several distinct sections, namely an Analysis bank 200, M-fold decimator 210, subband processors 220, M-fold expander 230 and a Synthesis bank 240. The input signal x(n) is coupled to the Analysis bank 200 for each channel, where H(z) is an abbreviation of H(ejxcfx89). The subband processors Pi 220 are normally quantizers in this example, but can represent other operators.
FIG. 2b refers to a uniform filter bank with polyphase filters. A delay chain 250 feeds the set of M filters 260, Hk(z), which is considered orthonormal if the polyphase matrix 270 E(ejxcfx89) is unitary for all xcfx89. The subband processors 280 are disposed between the polyphase matrices 270, 290. The decimators 260 are considered uniform in this example as they are identical to each other. The expanders 300 are essentially inverse of the decimators 260 in this example. A biorthogonal filter bank system exists if the matrix R(ejxcfx89) 290 is the inverse of E(ejxcfx89) 270 for all xcfx89.
The division of the wide frequency band into narrow channels is sometimes performed using uniform polyphase filter banks. The highest RF frequency that can be processed is generally limited by the sampling rate capability of the polyphase filters. The Nyquist rate in most applications is the minimum sampling rate at which a particular RF frequency can be measured, and is equal to twice the particular RF frequency. The bank of polyphase filters must be able to run at the Nyquist rate corresponding to the highest frequency of the RF band of the receiver, and the reason that a filter bank would be operated at this rate is that this is the slowest rate at which it can be operated to cover the receiver""s RF frequency band, and determine the clock rate for which the hardware must be designed. In general, minimizing the hardware clock rate reduces hardware costs.
Digital receivers using uniform polyphase filter banks operating at the Nyquist rate suffer from the problem of aliasing between channels. Aliasing is a well-known problem in digital systems, and alters frequencies outside the Nyquist bandwidth map to frequencies that are either higher or lower than the actual frequency of the received signal. One way of eliminating aliasing between channels is to oversample the received signal and run the hardware including the polyphase filter banks at a rate exceeding the Nyquist rate. However, oversampling the signal and running the hardware at the higher rate is not desirable because it makes building the hardware for a wide frequency bandwidth (e.g., 1 GHz) costly or difficult, if not impossible with current technology.
Another way of eliminating aliasing between channels for a given RF signal bandwidth is to employ filters with narrower frequency bins (i.e., xe2x80x9cnarrowerxe2x80x9d filters) and employ a proportionately greater number of such narrower filters in the polyphase filter bank. However, narrowing the filters and increasing their number is not desirable because it increases the physical size of the hardware, and therefore increases the power consumption and heat dissipation.
The digital channelized receiver has several known limitations. A first limitation is caused by the structure of the filter bank and the pulsed nature of the input signals. In order to have continuous coverage across the instantaneous bandwidth, adjacent channel responses are overlapped to a large degree. In this respect, the channelized receiver acts like a spectrum analyzer. Thus, there is a great deal of crosstalk between the channels, even when the input is a simple continuous wave signal. This situation is exacerbated when a pulsed signal is input because the leading and trailing edges of the pulse contain a great deal of broad band energy which spills into adjacent and non-adjacent channels, and the out-of-channel, time-domain output responses have a peak on the leading and trailing edges of the pulse due to the impulse response of the filters. Due to these combined effects there is a second limitation in that there must be some method to xe2x80x9carbitratexe2x80x9d between the filter channels and determine in which channel the input signal truly resides. The remaining responses are then classified as out-of-channel responses and discarded.
The frequency resolution capability or the ability to resolve and process two signals closely spaced in frequency, is limited by the receiver""s arbitration capability. Currently, techniques such as amplitude comparison of adjacent channels and techniques that detect the presence of the xe2x80x9crabbit-earxe2x80x9d effect have been used to perform channel arbitration. Both of these approaches use only the amplitudes of filter bank outputs and have inherent limitations. Implementation of a known architecture, described by L. R. Rabiner and R. E. Crochiere in xe2x80x9cMulti-Rate Digital Signal Processingxe2x80x9d, Prentis Hall, Englewood Cliffs, N.J., 1983, which could provide accurate arbitration capability, requires an inefficient number of decimators, expanders and polyphase filter components to be practical within the context of the digital receiver.
There have been various attempts to alleviate the problems described herein. The concept of a digital, channelized instantaneous frequency measurement receiver is further described in U.S. Pat. No. 5,499,391. For example, a basestation transceiver can implement a high speed analog-to-digital (A/D) converter and equipment which makes use of efficient digital filtering algorithms such as the Fast Fourier Transform (FFT) to separate the incoming signal energy into multiple baseband channels. On the transmit side, this implementation includes an inverse FFT processing combiner that outputs a combined signal representative of the contents of the baseband signal provided to it.
In U.S. Pat. No. 6,356,569, a digital channelizer with an arbitrary output sampling frequency is described. The digital channelizer uses a polyphase filter element in which a shift register is used to commutate time series data to a bank of polyphase filters.
In U.S. Pat. No. 6,393,451, a block compensator is inserted in the channelizer/de-channelizer chain, wherein the block compensator corrects phase continuity problems thereby increasing the flexibility of the modified fast convolutional algorithm.
A channelizer receiver is disclosed in U.S. Pat. No. 6,085,077, wherein an optimized filter bank allows simple channel arbitration. Another wideband channelizer receiver incorporating a diversity switch in detailed in U.S. Pat. No. 5,577,031 wherein the strongest signals is connected for processing.
Previous channelized systems used only single bin time domain reconstruction or narrowband set-on receivers. The signal bandwidth and center frequencies have to be matched to the channelization of the signals of interest. Asset usage for set-on assets becomes prohibitive for dense environments. The inefficiency of processing and misallocation of resources increases costs and delays processing as well as not allowing wideband efficient coverage.
The invention is devised in the light of the problems of the prior art described herein. Accordingly it is a general object of the present invention to provide a novel and useful technique that can solve the problems described herein.
One object of the invention is a multirate filter bank analysis/synthesis filter set that allows a high performance signal detection capability with an alias free signal recombination capability for signals that span multiple frequency bins. Previous signal intelligence (SigInt) systems have required separate assets dedicated for the wideband signal detection, with additional set-On receiver assets used for narrowband exploitation functions, such as Recognition, DF, etc . . . The present invention allows the use of a single wideband asset to provide for data channelized for detection processing with the ability to recombine one or more adjacent frequency bins into a wider bandwidth baseband time domain data stream suitable for exploitation processing.
The present implementation allows the use of an efficient partial band reconstruction mechanism that allows signal reconstruction using only the frequency subchannels that pertain to the signal of interest that is to be copied. The filter design mechanism utilizes the ability to separate the specification of the analysis filter to support signal detection in environments of high dynamic range. The signal reconstruction (synthesis) filter, since it utilizes fewer bins, is able to support most of the burden required for low mean squared error signal reconstruction (eg: a higher order filter).
The ability and design of filters in support of partial reconstruction is one of the overall aims of the present invention. The design solutions of the prior art do not address the conditions and requirements of the present invention and are generally unable to accommodate the partial band reconstruction described herein. Employing FFT banks of a high number of channels and operating in a high dynamic range requirements, the channelized data is filtered and if there is not a high stop band attenuation then signals create interference with other channels. Thus, a high stop band attenuation, such as 80-90 dB in the channelizer path is needed.
The analysis bank high dynamic range is not accounted for in the prior art that generally discusses a 20 dB dynamic range. The present invention has dynamic range of approximately 90 dB on the analysis side and 50 dB on the reconstruction side.
The filters on the analysis side and synthesis side that perform the desired processing taking into account the requirements and with a sample rate that is not too high to be prohibitive. Other methods assume real value signals as opposed to complex values and others simply cannot satisfy the constraints of the present invention.
One object is the separation of analysis/synthesis filter specification. Another object is that the multibin reconstruction performance is driven by the synthesis filter bank which has lower computational requirements than the analysis filter, as the synthesis filter only uses the frequency subchannels pertaining to the signal of interest.
Still other objects and advantages of the present invention will become readily apparent to those skilled in this art from the following detailed description, wherein we have shown and described only a preferred embodiment of the invention, simply by way of illustration of the best mode contemplated by us on carrying out our invention. As will be realized, the invention is capable of other and different embodiments, and its several details are capable of modifications in various obvious respects, all without departing from the invention.
The features and advantages described herein are not all-inclusive and, in particular, many additional features and advantages will be apparent to one of ordinary skill in the art in view of the drawings, specification, and claims. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and not to limit the scope of the inventive subject matter.